Large numbers of semiconductor devices are commonly used in a single piece of electronic equipment or product, and these semiconductor devices often handle the primary functions of the electronic equipment such that high reliability of the semiconductor devices has become ever more important as reliance on electronic equipment increases for everyday functions. Generally the reliability of semiconductor devices depends on their resistance to stresses applied to the devices, such as electric stress, thermal stress, mechanical stress, and environmental stress (humidity, etc.). If part of a semiconductor device has a defect or particularly weak structure, the defect or weak structure may react adversely to the applied stress, and such an adverse reaction may cause failures in the semiconductor device.
Semiconductor devices have failure mechanisms dependent on product use conditions or the various stresses applied to the devices that are unique to semiconductors, and resolving these problems during the process development stage is an important element for providing high reliability of the semiconductor devices. For example, typical failure mechanisms that can pose problems in the process development stage of semiconductor devices may include time-dependent dielectric breakdown (TDDB), hot carrier injection (HCI), biased temperature instability (BTI), soft error rate (SER), retention disturbance, electromigration (EM), stress migration (SM), and TDDB between metal lines.
More specifically, TDDB may cause reliability issues within gate dielectric film (i.e., process element) of the semiconductor device because bias applied to a gate electrode for a long period of time may produce defects in the gate dielectric film that increase micro leak current and the eventual breakdown of the dielectric. HCI may cause reliability issues within the transistor (i.e., process element) of the semiconductor device because high-energy electrons and holes generated by impact ionization of electrons accelerated by high electric fields may be trapped in the oxide film causing transistor characteristics to fluctuate. BTI may cause reliability issues within the transistor of the semiconductor device because application of a bias at high temperatures may increase the interface state and fixed charge causing the transistor characteristics to fluctuate.
SER may cause reliability issues within the memory device (i.e., process element) of the semiconductor device because high-energy cosmic ray particles may cause memory data rewrite errors, which is typically a temporary data error. Retention disturbance may cause reliability issues within the memory device of the semiconductor device because long-term storage or operating environment stress may cause the trapped charge in a Flash memory to disappear inverting the data. EM may cause reliability issues within the metal lines (i.e., process element) of the semiconductor device because the physical impacts between electrons and metal atoms cause the metal atoms to move, creating voids in the metal lines. SM may cause reliability issues within the metal lines of the semiconductor device because vacancies (e.g., atom holes) in copper lines due to metal line stress may induce a creep phenomenon causing voids to form and grow. Lastly, TDDB between metal lines may cause reliability issues within the interlayer films of the semiconductor device because dielectric breakdown may result in a short-circuit between metal lines.
Reliability device simulators are capable of modeling these failure mechanisms and have become an integral part of the design process of semiconductor devices. For example, the failure mechanisms may be modeled using the simulators during the semiconductor device design process in order to set fail rates such that the semiconductor device may operate reliably for a minimum expected useful life. The semiconductor device reliability may be measured by failure rate in FIT. The FIT is a unit, defined as one failure per billion part hours. The semiconductor industry typically provides an expected FIT for every product that is sold based on operation within the specified conditions of voltage, frequency, heat dissipation and etc. Hence, a semiconductor device reliability model is a prediction of the expected mean time between failures (MTBF) for a semiconductor device as the reciprocal of the sum of the FIT rates for every component.
Conventionally, reliability failure mechanisms are evaluated as the semiconductor device technology is developed, and one fail rate may be set for the entire manufacturing process distribution for each of the failure mechanisms. Thereafter, all of fail rates set for the individual failure mechanisms are combined together to set one fail rate for the semiconductor device. Stable semiconductor device reliability may be provided by verifying the required reliability when developing each process element and reflecting these results in the design rules of the semiconductor device.
However, the conventional processes for verifying semiconductor device reliability do not account for variation as a function of the process window (e.g., fast or slow based on front end of the line (FEOL) or back end of the line (BEOL) processes). For example, some reliability failure mechanisms have a probability of occurrence that changes through a process window distribution. Specifically, BTI and HCI vary as a function of the FEOL process window whereby there are more fails seen at the slow end of the process distribution. On the other hand, TDDB and EM also vary as a function of the FEOL process window, but there are more fails seen at the fast end of the process distribution. Additionally, some failure mechanisms do not vary as a function of the process window but instead may have relationships to other process window variation, e.g., stress voids (via size, metal content), defects (overlay, pitch), and chip package interaction (CPI) (metal content).
Conventional reliability processes comprises a composite of failure rate analysis based on multiple failure mechanisms that are typically overbound or underbound because the reliability models are performed on a single set of hardware or semiconductor devices, and do not consider where the hardware or semiconductor devices fall within the manufacturing process window distribution. For example, when conventional models are run with limits (e.g., worst case parameters) in the specific process window in which they are bounded, the models are not capable of accurately portraying what the reliability output of the entire manufacturing line may be. Therefore, the conventional reliability models may not reflect true product reliability.
Accordingly, there exists a need in the art to overcome the deficiencies and limitations described herein above.